Results 41 to 50 of about 24,030 (229)

Bregman iterative regularization using model functions for nonconvex nonsmooth optimization

Frontiers in Applied Mathematics and Statistics, 2022
In this paper, we propose a new algorithm called ModelBI by blending the Bregman iterative regularization method and the model function technique for solving a class of nonconvex nonsmooth optimization problems.
Haoxing Yang, Hui Zhang, Hongxia Wang, Lizhi Cheng   +3 more
doaj   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

The Barzilai and Borwein gradient method with nonmonotone line search for nonsmooth convex optimization problems

Mathematical Modelling and Analysis, 2012
The Barzilai and Borwein gradient algorithm has received a great deal of attention in recent decades since it is simple and effective for smooth optimization problems. Whether can it be extended to solve nonsmooth problems?
Gonglin Yuan, Zengxin Wei
doaj   +1 more source

A Fast Gradient and Function Sampling Method for Finite Max-Functions

, 2017
This paper tackles the unconstrained minimization of a class of nonsmooth and nonconvex functions that can be written as finite max-functions. A gradient and function-based sampling method is proposed which, under special circumstances, either moves ...
Helou, Elias S., Santos, Sandra A., Simões, Lucas E. A.   +2 more
core   +1 more source

A Novel Contact‐Implicit Trajectory Optimization Framework for Quadruped Locomotion without Fixed Contact Sequences

Advanced Intelligent Systems, EarlyView.
Legged robots have advanced in environmental interaction through contact, but most works rely on fixed contact sequences. This work presents a new method based on an indirect optimization method for legged robots to automatically generate contact sequences for complex movements.
Yaowei Chen, Jie Zhang, Ming Lyu
wiley   +1 more source

Nonsmooth Implicit Differentiation for Machine Learning and Optimization [PDF]

, 2021
Jérôme Bolte, Tam Le, Edouard Pauwels, Antonio Silveti-Falls   +3 more
openalex   +1 more source

Adaptive Machine Learning Framework for Optimizing the Affinity Purification of Adeno‐Associated Viral Vectors

Biotechnology and Bioengineering, EarlyView.
ABSTRACT Adeno‐associated viral (AAV) vectors for gene therapy are becoming integral to modern medicine, providing therapeutic options for diseases once deemed incurable. Currently, viral vector purification is a critical bottleneck in the gene therapy industry, impacting product efficacy and safety as well as accessibility and cost to patients ...
Kelvin P. Idanwekhai, Shriarjun Shastry, Morgan R. Hurst, Arianna Minzoni, Eduardo Barbieri, Luke Remmler, Eugene N. Muratov, Michael A. Daniele, Stefano Menegatti, Alexander Tropsha   +9 more
wiley   +1 more source

Substantiation of the backpropagation technique via the Hamilton—Pontryagin formalism for training nonconvex nonsmooth neural networks

Доповiдi Нацiональної академiї наук України
The paper observes the similarity between the stochastic optimal control over discrete dynamical systems and the lear ning multilayer neural networks. It focuses on contemporary deep networks with nonconvex nonsmooth loss and activation functions.
V.I. Norkin
doaj   +1 more source

Transfer Learning Approaches in Bioprocess Engineering: Opportunities and Challenges

Biotechnology and Bioengineering, EarlyView.
ABSTRACT Transfer learning (TL) has recently emerged as a promising approach to overcoming one of the key limitations of bioprocess engineering: data scarcity. By leveraging knowledge from one bioprocess to another, TL allows existing models and data sets to be reused efficiently, accelerating process development, improving prediction accuracy, and ...
Daniel Barón Díaz, Anna‐Lena Drommershausen, Alexander Grünberger, Dirk Holtmann   +3 more
wiley   +1 more source

Forward-backward truncated Newton methods for convex composite optimization [PDF]

, 2014
This paper proposes two proximal Newton-CG methods for convex nonsmooth optimization problems in composite form. The algorithms are based on a a reformulation of the original nonsmooth problem as the unconstrained minimization of a continuously ...
Bemporad, Alberto, Patrinos, Panagiotis, Stella, Lorenzo   +2 more
core   +1 more source